Lamina v0.1.4 — portable Ornith and image support

v0.1.4

Choose Qwen3.6-35B-A3B or Ornith-1.5-35B-A3B in the portable Windows ZIP.
Both support text, tools, reasoning and image input. Python, the engine and
the CPU image encoder are included; no compiler or CUDA toolkit is needed.
Setup downloads the selected model and its own verified image projector.

START-HERE.bat --reconfigure asks for model, context and MTP again; Enter
keeps each saved choice. The README explains setup, saved settings and coding
clients, including advertising image support in pi's model configuration.

Retain the full 128K context option and include the measured expert-admission
scheduling improvements. No model math, quantization or history truncation is
changed. Image preprocessing uses sufficient resolution for text reading;
CPU encoding can take a minute or more on older CPUs. Compiled GPU coverage is
RTX 30/40/50; this release is tested on RTX 4060, with other generations pending.

Validated on RTX 4060 8 GB / Ryzen 7 1700X / 64 GB RAM: 51 Python tests, default CMake/lamina-gguf, native sampling/CUDA elementwise/attention, and extracted portable startup at 128K capacity with MTP, SSE text/usage, streamed tools, reasoning and prefix reuse for both models. Both models read the image fixture; the extracted portable Ornith image request also passed with the application in a folder containing spaces and PATH limited to Windows system directories. First image responses took about 84–87 seconds on this older CPU. This is a functional check, not a full-context speed or general OCR accuracy claim. RTX 30/50 runtime remains unverified.